Events
Feb 5 - Feb 11, 2023
Jan 29 - Feb 4, 2023
Driving Innovation by Simulation
Dr. Emad Dlala, Vice President Powertrain, Lucid Motors Co.
B9 L3 R3128
Jan 1 - Jan 7, 2023
Dec 4 - Dec 10, 2022
Nov 27 - Dec 3, 2022
Nov 20 - Nov 26, 2022
Nov 13 - Nov 19, 2022
Nov 6 - Nov 12, 2022
Oct 30 - Nov 5, 2022
Oct 23 - Oct 29, 2022
Oct 16 - Oct 22, 2022
Inference for Longitudinal Data After Adaptive Sampling
Prof. Susan Murphy, Statistics and Computer Science and Radcliffe Alumnae Professor at the Radcliffe Institute, Harvard University
B9 L2 H2
We used Reinforcement Learning; but did it work?
Prof. Susan Murphy, Statistics and Computer Science and Radcliffe Alumnae Professor at the Radcliffe Institute, Harvard University
B9 L2 H2
Oct 9 - Oct 15, 2022
Oct 2 - Oct 8, 2022
Sep 25 - Oct 1, 2022
Sep 18 - Sep 24, 2022
Sep 11 - Sep 17, 2022
Sep 4 - Sep 10, 2022
Aug 28 - Sep 3, 2022
Jun 26 - Jul 2, 2022
Jun 5 - Jun 11, 2022
May 29 - Jun 4, 2022
Differentially private testing of symmetry equivalence hypotheses based on the characteristic function
Prof. Simos G. Meintanis, University of Athens
B1 L4 R4102
Apr 24 - Apr 30, 2022
Time-domain and frequency-domain approaches for multiple and multivariate time series - Lecture 3
Prof. Raquel Prado, Department of Statistics, University of California
B1 L4 R4102
Conditionally Gaussian dynamic models, non-linear models and multi-process models for univariate time series - Lecture 2
Prof. Raquel Prado, Department of Statistics, University of California
B1 L4 R3119
Spatio-Temporal Statistical Models Using Integro-Differential Equations
Prof. Bruno Sanso, Department of Statistics, University of California
B1 L4 R4102
Dynamic linear models: Theory, computation and case studies - Lecture 1
Prof. Raquel Prado, Department of Statistics, University of California
B1 L4 R4102
Model Survival Data with high and ultrahigh dimensional predictors: feature screening and statistical inference - Lecture 2
Yi Li, Professor, Biostatistics, University of Michigan
B1 L4 R4102
Apr 17 - Apr 23, 2022
Gaussian Graphical Regression with High-Dimensional Responses and Covariates
Yi Li, Professor, Biostatistics, University of Michigan
B2 B3 A0215
Enhancing mixing in binary fluids
Prof. Peter J. Schmid, Professor, Mechanical Engineering, KAUST
B9 L2 H2
Regularized Regression for Survival Data: Methods and Applications
Yi Li, Professor, Biostatistics, University of Michigan
B1 L4 R4102
Apr 10 - Apr 16, 2022
Biomedical research: a world of statistical challenges
Prof. David Gomez-Cabrero, Biological, Environmental Science and Eng, KAUST
B9 L2 H2
